Price: $40.00 – $34.83
(as of Dec 24,2024 14:30:42 UTC – Details)
Publisher : Morgan & Claypool Publishers (November 1, 2014)
Language : English
Paperback : 126 pages
ISBN-10 : 1627052011
ISBN-13 : 978-1627052016
Item Weight : 8.5 ounces
Dimensions : 7.5 x 0.29 x 9.25 inches
Graph-Based Semi-Supervised Learning: A Comprehensive Guide (Synthesis Lectures on Artificial Intelligence and Machine Learning, 29)
In the world of machine learning, semi-supervised learning is a powerful technique that leverages both labeled and unlabeled data to improve model performance. One particular approach that has gained popularity in recent years is graph-based semi-supervised learning.
In our latest edition of the Synthesis Lectures on Artificial Intelligence and Machine Learning, we delve into the intricacies of graph-based semi-supervised learning. This comprehensive guide covers the fundamentals of graph theory, the principles of semi-supervised learning, and how these two concepts intersect to create effective machine learning models.
With contributions from leading experts in the field, this book provides a thorough overview of the latest advancements in graph-based semi-supervised learning. Readers will gain insights into the different types of graphs used in machine learning, the algorithms that drive graph-based semi-supervised learning, and real-world applications of this technique.
Whether you’re a seasoned machine learning practitioner or a newcomer to the field, this book offers valuable insights and practical guidance on how to leverage graph-based semi-supervised learning for improved model performance. Stay ahead of the curve and pick up your copy of Graph-Based Semi-Supervised Learning today!
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